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• Expected Free Energy (EFE) can be reduced to Upper Confidence Bound (UCB), Lower Confidence Bound (LCB), and Expected Information Gain (EIG) under specific assumptions.result 95%
• Expected Free Energy (EFE) possesses unbiased convergence guarantees for concave functions.result 95%
• A novel curvature-aware update rule for Expected Free Energy (EFE) is introduced.method 95%
• The proposed adaptive (curvature-aware) EFE acquisition function outperforms state-of-the-art acquisition functions for joint optimization and learning.result 95%
• The adaptive Expected Free Energy acquisition function achieves the least final simple regret and error in learning the Gaussian process compared to state-of-the-art methods.result 95%
• The curvature-aware update rule for EFE encourages resampling in high curvature regions and exploration in uncertain regions with low curvature.method 90%
• The stationary point of Expected Free Energy (EFE) is curvature agnostic.result 85%

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